Estimating effective population size trajectories from time-series identity-by-descent segments

Area of Science:

• Population Genetics
• Ancient DNA Analysis
• Demographic Inference

Background:

• Identity-by-descent (IBD) segments indicate shared ancestry and are used for demographic inference in modern DNA.
• Recent advances allow IBD analysis in ancient DNA (aDNA), enabling historical population studies.
• Existing aDNA demographic methods often assume contemporaneous sampling, which is not realistic for time-series data.

Purpose of the Study:

• To develop a novel method, Ttne (Time-Transect Ne), for inferring effective population size trajectories from aDNA using time-transect sampling.
• To enhance the resolution of demographic inference by incorporating IBD sharing across time-series aDNA data.
• To address and model IBD detection errors prevalent in empirical aDNA analyses.

Main Methods:

• Developed Ttne, a method modeling time-transect sampling for inferring population size trajectories.
• Utilized simulations to validate the increased resolution of time-series IBD sharing compared to contemporaneous methods.
• Implemented an approach to estimate and model IBD detection errors for robust analysis.

Main Results:

• Simulations demonstrated that time-series IBD sharing provides higher resolution for inferring recent effective population size fluctuations.
• Ttne was applied to aDNA time transects from the Copper Age Corded Ware Culture and Medieval England.
• Both case studies revealed evidence of population growth, aligning with archaeological findings.

Conclusions:

• Ttne effectively models time-transect sampling for accurate demographic inference from aDNA.
• The method successfully identified population growth in distinct ancient European populations.
• This approach enhances our ability to reconstruct detailed population histories using IBD sharing in aDNA.